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Emergent Lag Phase in Flux-Regulation Models of Bacterial Growth

Lag phase is observed in bacterial growth during a sudden change in conditions: growth is inhibited whilst cells adapt to the environment. Bi-phasic, or diauxic growth is commonly exhibited by many species. In the presence of two sugars, cells initially grow by consuming the preferred sugar then und...

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Autores principales: Bate, Fiona, Amekan, Yumechris, Pushkin, Dmitri O., Chong, James P. J., Bees, Martin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10425510/
https://www.ncbi.nlm.nih.gov/pubmed/37580520
http://dx.doi.org/10.1007/s11538-023-01189-6
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author Bate, Fiona
Amekan, Yumechris
Pushkin, Dmitri O.
Chong, James P. J.
Bees, Martin
author_facet Bate, Fiona
Amekan, Yumechris
Pushkin, Dmitri O.
Chong, James P. J.
Bees, Martin
author_sort Bate, Fiona
collection PubMed
description Lag phase is observed in bacterial growth during a sudden change in conditions: growth is inhibited whilst cells adapt to the environment. Bi-phasic, or diauxic growth is commonly exhibited by many species. In the presence of two sugars, cells initially grow by consuming the preferred sugar then undergo a lag phase before resuming growth on the second. Biomass increase is characterised by a diauxic growth curve: exponential growth followed by a period of no growth before a second exponential growth. Recent literature lacks a complete dynamic description, artificially modelling lag phase and employing non-physical representations of precursor pools. Here, we formulate a rational mechanistic model based on flux-regulation/proteome partitioning with a finite precursor pool that reveals core mechanisms in a compact form. Unlike earlier systems, the characteristic dynamics emerge as part of the solution, including the lag phase. Focussing on growth of Escherichia coli on a glucose–lactose mixture we show results accurately reproduce experiments. We show that for a single strain of E. coli, diauxic growth leads to optimised biomass yields. However, intriguingly, for two competing strains diauxic growth is not always the best strategy. Our description can be generalised to model multiple different microorganisms and investigate competition between species/strains.
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spelling pubmed-104255102023-08-16 Emergent Lag Phase in Flux-Regulation Models of Bacterial Growth Bate, Fiona Amekan, Yumechris Pushkin, Dmitri O. Chong, James P. J. Bees, Martin Bull Math Biol Original Article Lag phase is observed in bacterial growth during a sudden change in conditions: growth is inhibited whilst cells adapt to the environment. Bi-phasic, or diauxic growth is commonly exhibited by many species. In the presence of two sugars, cells initially grow by consuming the preferred sugar then undergo a lag phase before resuming growth on the second. Biomass increase is characterised by a diauxic growth curve: exponential growth followed by a period of no growth before a second exponential growth. Recent literature lacks a complete dynamic description, artificially modelling lag phase and employing non-physical representations of precursor pools. Here, we formulate a rational mechanistic model based on flux-regulation/proteome partitioning with a finite precursor pool that reveals core mechanisms in a compact form. Unlike earlier systems, the characteristic dynamics emerge as part of the solution, including the lag phase. Focussing on growth of Escherichia coli on a glucose–lactose mixture we show results accurately reproduce experiments. We show that for a single strain of E. coli, diauxic growth leads to optimised biomass yields. However, intriguingly, for two competing strains diauxic growth is not always the best strategy. Our description can be generalised to model multiple different microorganisms and investigate competition between species/strains. Springer US 2023-08-14 2023 /pmc/articles/PMC10425510/ /pubmed/37580520 http://dx.doi.org/10.1007/s11538-023-01189-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Article
Bate, Fiona
Amekan, Yumechris
Pushkin, Dmitri O.
Chong, James P. J.
Bees, Martin
Emergent Lag Phase in Flux-Regulation Models of Bacterial Growth
title Emergent Lag Phase in Flux-Regulation Models of Bacterial Growth
title_full Emergent Lag Phase in Flux-Regulation Models of Bacterial Growth
title_fullStr Emergent Lag Phase in Flux-Regulation Models of Bacterial Growth
title_full_unstemmed Emergent Lag Phase in Flux-Regulation Models of Bacterial Growth
title_short Emergent Lag Phase in Flux-Regulation Models of Bacterial Growth
title_sort emergent lag phase in flux-regulation models of bacterial growth
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10425510/
https://www.ncbi.nlm.nih.gov/pubmed/37580520
http://dx.doi.org/10.1007/s11538-023-01189-6
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